What is it, architecture, market players and it’s future
Nowadays companies are storing a huge amount of data from their business operations. Many of these organisations don’t even use this data which leads to missing the chance of increasing their revenue dramatically. To gain profit from that information usually the people in an organisation use software programs such as Excel and different database applications for various departments through the organisation. This method is time-consuming and far more ineffective in comparison with the so-called Business Intelligence service.
In a world where everything is happening so fast and the need of the right information at the right time means competitive advantage, integration of a Business Intelligence solution is crucial for an organisation.
What is Business Intelligence(BI)?
It is a term that covers processes, methods, measurements and systems that corporations use to more easily view, analyze and understand information relevant to the history, current performance and future projection of the business. Getting knowledge of the past and current situation helps managers choose the right decisions more easily and on time which will lead to unlock the full potential of an organisation.
Business Intelligence technology stack
The technology stack is designed to highlight the different layers of technology that will be affected by a BI project, all the way from the various data sources which is the bottom of the stack to the portal product used to present information to users at the top.
1. Applications and data sources – this is the data that is generated from the business applications operations. It should implement a way of processing data from various data sources with most using proprietary data formats. The unnecessary part of the source data must be removed and organised. The common data sources are Customer Relationship Management(CRM), Supply Chain Management(SCM) and Enterprise Resource Planning(ERP) systems.
2. Data integration – the process of collecting data from various data sources and its storage in a central repository called Datawarehouse. This work is done by Extract, Transform and Load(ETL) tools.
3. Relational/Column-oriented databases and data warehouses – the data is stored and organized tactical or historical in a database(Datawarehouse). This database contains all of the organisation information after the unnecessary part of the data is removed.
4. OLAP applications and analytic engines  – Online analytic processing (OLAP) applications provide a layer of separation between the storage repository and the end user’s analytic application. Its role is to perform special analytical functions that require high-performance processing power and more specialized analytical skills.
5. Analytic applications – the programs used to run queries against the data to perform either “slide-and-dice” analysis of historical data or more predictive analyses, often referred to as “drill-down” analysis. For example, a customer intelligence application might enable a historical analysis of customer orders and payment history. Alternatively, users could drill down to understand how changing a price might affect future sales in a specific region.
6. Reporting applications – this is the top layer of a BI stack. It represents the data that was queried in a visual way(tables, charts etc.). In many cases, different scenarios are organised in a form of reports or dashboards  which are executed for a particular time or other relevant to the organisation dimension.
More about the BI players and trends in my next blog.
Something interesting to add about BI? Leave your comments below
